For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
10
views
1
references
 Top references
cited by
7
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      1,535
      similar
       All similar
      • Record: found
      • Abstract: not found
      • Article: not found

      DeNNeS: deep embedded neural network expert system for detecting cyber attacks

      Author(s): ,
      Publication date (Electronic):
      Journal: Neural Computing and Applications
      Publisher: Springer Science and Business Media LLC

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Related collections

          Most cited references1

          • Record: found
          • Abstract: not found
          • Book: not found

          Neural network learning and expert systems. A Bradford book

          SI Gallant (1995)
          Book 0 comments Cited 1 times – based on 0 reviews
            Bookmark
            All references

            Author and article information

            Contributors
            Samaneh Mahdavifar: (View ORCID Profile)
            Journal
            Title: Neural Computing and Applications
            Abbreviated Title: Neural Comput & Applic
            Publisher: Springer Science and Business Media LLC
            ISSN (Print): 0941-0643
            ISSN (Electronic): 1433-3058
            Publication date Created: September 2020
            Publication date (Electronic): March 28 2020
            Publication date (Print): September 2020
            Volume: 32
            Issue: 18
            Pages: 14753-14780
            Article
            DOI: 10.1007/s00521-020-04830-w
            SO-VID: c2800e72-5411-473b-a5ed-202a49415d2e
            Copyright © © 2020
            License:

            http://www.springer.com/tdm

            http://www.springer.com/tdm

            History

            Data availability:

            Comments

            Comment on this article

            scite_

            Similar content1,535

            See all similar

            Cited by6

            See all cited by

            Most referenced authors1

            See all reference authors